•Example (Pearl, 1988) You have a new burglar alarm at home that is quite reliable at detecing burglars but may also respond at times to an earthquake. You also have two neighbours, John and Mary, who promise to call you at work when they hear the alarm. John always calls when he hears the alarm but sometimes confuses the telephone ringing with the alarm and calls then. Also, Mary likes loud music and sometimes missed the alarm. Given the evidence of who has or has not called, we would like to estimate the probability of a burglary.
Question: Who is more reliable when burglary happened? Mary or John? Proof it by calc. using Bayesian Network
From calculation above, we obtain; P(JohnCalls|Burglary) = P (J|B) = 0.85 P(MaryCalls|Burglary) = P (M|B) =0.66 # Since P (J|B) is greater than P (M|B) therefore, John is more reliable than Mary.
You have a new burglar alarm at home that is quite reliable at detecing burglars but may also respond at times to an earthquake. You also have two neighbours, John and Mary, who promise to call you at work when they hear the alarm. John always calls when he hears the alarm but sometimes confuses the telephone ringing with the alarm and calls then. Also, Mary likes loud music and sometimes missed the alarm. Given the evidence of who has or has not called, we would like to estimate the probability of a burglary.
Question: Who is more reliable when burglary happened? Mary or John? Proof it by calc. using Bayesian Network
From calculation above, we obtain;
P(JohnCalls|Burglary) = P (J|B) = 0.85
P(MaryCalls|Burglary) = P (M|B) = 0.66
# Since P (J|B) is greater than P (M|B) therefore, John is more reliable than Mary.
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